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To promote residents' waste separation behavior, waste separation supervision has been a crucial need. This paper aims to explore the supervision mechanism of residents' waste separation behavior using a tripartite evolutionary game model. The evolutionary stability conditions of resident, property service enterprise, and the government were analyzed. The influences of the main parameters on the strategy of three stakeholders were explored through numerical simulation. The results show that the regulatory mechanism of waste separation will reach the optimal stable strategy when the following conditions are satisfied: (1) the penalty for nonclassification is higher than the difference between classification cost and the total benefit of classification; (2) the subsidy to property services enterprise is greater than the total cost of positive participation management. Residents' behaviors are mainly influenced by rewards and punishments. The behavioral strategies of property service companies are more sensitive to subsidies than penalties. In the early stage of mandatory waste separation, it is important to reduce the cost of residents' separation, develop the publics' environmental awareness, and increase the willingness of properties to participate in management. This paper presents a new perspective and theoretical guidelines for the local government and communities to supervise residents' waste separation behaviors in China and other developing countries and offers useful insights into waste separation management for other countries. [ABSTRACT FROM AUTHOR]

An index for reporting air quality is called the air quality index (AQI). It measures the impact of air pollution on a person's health over a short period of time. The purpose of the AQI is to educate the public on the negative health effects of local air pollution. The amount of air pollution in Indian cities has significantly increased. There are several ways to create a mathematical formula to determine the air quality index. Numerous studies have found a link between air pollution exposure and adverse health impacts in the population. Data mining techniques are one of the most interesting approaches to forecast AQI and analyze it. The aim of this paper is to find the most effective way for AQI prediction to assist in climate control. The most effective method can be improved upon to find the most optimal solution. Hence, the work in this paper involves intensive research and the addition of novel techniques such as SMOTE to make sure that the best possible solution to the air quality problem is obtained. Another important goal is to demonstrate and display the exact metrics involved in our work in such a way that it is educational and insightful and hence provides proper comparisons and assists future researchers. In the proposed work, three distinct methods—support vector regression (SVR), random forest regression (RFR), and CatBoost regression (CR)—have been utilized to determine the AQI of New Delhi, Bangalore, Kolkata, and Hyderabad. After comparing the results of imbalanced datasets, it was found that random forest regression provides the lowest root mean square error (RMSE) values in Bangalore (0.5674), Kolkata (0.1403), and Hyderabad (0.3826), as well as higher accuracy compared to SVR and CatBoost regression for Kolkata (90.9700%) and Hyderabad (78.3672%), while CatBoost regression provides the lowest RMSE value in New Delhi (0.2792) and the highest accuracy is obtained for New Delhi (79.8622%) and Bangalore (68.6860%). Regarding the dataset that was subjected to the synthetic minority oversampling technique (SMOTE) algorithm, it is noted that random forest regression provides the lowest RMSE values in Kolkata (0.0988) and Hyderabad (0.0628) and higher accuracies are obtained for Kolkata (93.7438%) and Hyderabad (97.6080%) in comparison to SVR and CatBoost regression, whereas CatBoost regression provides the highest accuracies for New Delhi (85.0847%) and Bangalore (90.3071%). This demonstrated definitely that datasets that had the SMOTE algorithm applied to them produced a higher accuracy. The novelty of this paper lies in the fact that the best regression models have been picked through thorough research by analyzing their accuracies. Moreover, unlike most related papers, dataset balancing is carried out through SMOTE. Moreover, all of the implementations have been documented via graphs and metrics, which clearly show the contrast in results and help show what actually caused the improvement in accuracy. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore the relationship between corporate social responsibility (CSR) and firm value in the Chinese market and identify factors that may influence it. We discuss the relationship between CSR engagement in Chinese firms and firm value from a nonlinear perspective. In addition, we examine how the degree of internationalization in a firm may affect the relationship between CSR and firm value. We employ the Hausman test to compare a random-effects and a fixed-effects model, and after testing and comparison, the fixed-effects model was chosen in our paper. Using data from 314 firms listed in China's A-shares market from 2010 to 2017, we verify the U-shaped relationship between CSR and firm value. Meanwhile, the degree of internationalization will affect firm value but cannot positively regulate the relationship between corporate social responsibility and firm value. [ABSTRACT FROM AUTHOR]

The application of artificial intelligence (AI) technology in the field of clothes can provide a good development mode and system under the social context of AI technology development. AI provides help for the development of intelligent clothing. Intelligent clothing is a high-tech product that integrates intelligent technology and clothing. It combines cutting-edge technologies in electronic information technology, sensor technology, textile science, and material science. In the extraction and analysis of environmental factors in clothing handicraft, AI technology has a considerable application prospect and a certain development potential. In order to improve the accuracy of environmental factors extraction in clothing handicraft, this paper uses convolutional neural network (CNN) to extract and analyze environmental factors in traditional clothing handicraft. We carried out experiments on the extraction of environmental factors in clothing handicrafts with pure color, few patterns, patterns, and complex background. The experimental results show that the CNN has a good effect on the extraction of environmental factors in clothing handicraft under different backgrounds. In addition, the model in this paper has good stability, accuracy, and feature extraction speed, which has high practical value and research significance. [ABSTRACT FROM AUTHOR]

In the rapid development of the country and schools, physical education and health programs have gradually become an essential part of schools in order to improve students' core physical education skills and literacy, and have a very important role and impact on students' physical and mental health development. The school P&H program not only conveys to teachers and students the knowledge and training skills to improve school sports and enhance physical fitness but also fully develops the awareness and ability of teachers and students to work hard and collaborate with each other. This paper examines and analyzes the problems and dilemmas associated with the pursuit of health and sport-specific intensity in school sports and combines theories of health and exercise, physical education, training, and moral education through literature review, logical analysis, and value analysis. The purpose of this paper is to clarify the different logics and orientations of specific sport intensity regulations, school sport health pursuits, and school sport teaching and to clarify and correct related issues, so as to provide theoretical and practical support for school sport to better implement the concept of "health first" and further promote school sport reform and sound development. In this paper, we analyze the relationship between exercise and health in physical education programs of teachers and schools from the perspective of natural dialectics and find out some outstanding problems that may exist in them, so as to effectively promote the development of students' physical and mental health. [ABSTRACT FROM AUTHOR]

As a compulsory course in universities, physical fitness is an important part of public health. At present, research on physical fitness lacks a comprehensive evaluation method, which cannot accurately guide public health. Based on this, this paper compares the key factors affecting public health, aiming to better guide public health and improve the level of public health. In this paper, 219 college students were selected as the research object, using statistical analysis methods, to find out the significant differences in influencing factors. Then, regression analysis is carried out on different influencing factors to determine the key factors affecting physical fitness. The results show that physical fitness level, exercise frequency, and physical injury are the key factors affecting physical fitness and have a serious impact on public health, with an impact level of about 70~80%. Therefore, colleges and sports departments should set out from the above factors, formulate a development plan for physical fitness, and promote the improvement of public health. [ABSTRACT FROM AUTHOR]

As the primary research vehicle, rural tourism is used in this paper to examine urban visitors' "homesickness." This research explores the effects of homesickness on tourists' perceptions of travel destinations and consumption intentions through qualitative analysis, logistic empirical analysis, and questionnaire survey. This work also explores the behavioral traits of customers' purchase intentions from the perspective of a "big data" environment, and it constructs the relevant consumption behavior model for rural visitors in accordance with those behavioral traits. Through questionnaire design and investigation, this paper makes statistical analysis on tourists' basic information, expected value, and actual experience and explores the related factors that affect their consumption behavior, so as to understand the consumption behavior law of tourists in rural tourism consumption. The research shows that the MSE (mean squared error) of this algorithm is about 4.16, and the RMSE (root mean square error) of this algorithm is about 0.508. Finally, combining the influence of tourists' consumption behavior, this paper tries to put forward some countermeasures and suggestions on rural tourism. This paper aims to study the development and planning of rural tourist destinations, and provide corresponding basis for the destination selection of tourists with homesickness. [ABSTRACT FROM AUTHOR]

Due to the successful holding of the Winter Olympics, China's enthusiasm for ice and snow sports has soared, and its enthusiasm for ice and snow tourism has also been further stimulated. At present, most of China's ice and snow tourism (IST) attractions are concentrated in the three eastern provinces. At the same time, due to the increasingly harsh environment, the natural landscape of IST is also shrinking. Therefore, this paper aims at studying the strategies of IST to optimize the ecological environment and economic growth from the perspective of sustainable development. First of all, this paper makes a certain introduction to the current situation of IST. After that, the current IST resources in China were analyzed, and the three northeastern provinces were taken as the research objects, and the distribution location, traffic conditions, and development trends of IST resources were studied in detail. Then, the autoregressive model is used to fit the tourism resources and tourist growth with the economic growth, and combined with the trend shown by the economic growth model, a strategy for the sustainable development of IST is proposed. The experimental results of this paper prove that the regional system attribute of IST resources and economic growth model is between 3 and 5, and the average is about 3.6, which shows that the growth of tourism resources has a positive correlation with economic growth. Therefore, from the perspective of sustainable development, the economic growth of the IST industry should also focus on the protection and humidity development of natural ice and snow landscapes. [ABSTRACT FROM AUTHOR]

In order to better understand the research and analysis of Nathaniel Hawthorne's landscape writing and ecological environment problems, his paper discusses the description of environmental landscape in Hawthorne's writings. This paper analyzes the "social-ecological" environment during the antebellum era through Hawthorne's literary writings. Comparing Hawthorne's writings of the landscape within statistics and diagrams, this study argues that the romantic descriptions of natural settings and characters in Hawthorne's writings reflect the social and ecological environment of antebellum era. Therefore, reads can accurately understand Nathaniel Hawthorne's living context and the ecological environment problems. This study also argues that Hawthorne's writings of landscape reflect much more the ecological and environmental problems in his era comparing with other antebellum writers. Understanding Hawthorne's writing of the environment will also provide a guidance for the contemporary society. [ABSTRACT FROM AUTHOR]

Western environmental philosophy was born out of the environmental movement that emerged in the second half of the 20th century, and it is fundamentally practical in orientation. However, over the past 50 years, the study of environmental philosophy has become increasingly abstract and theoretical and seems to have drifted away from the practice of environmental protection. At the beginning of the 21st century, Western environmental philosophy began to take a policy turn, with an increasing number of philosophers actively participating in national and international environmental policy discussions. This turn is the latest development in environmental pragmatism. However, the philosophy embodied in this turn is still weak and lacks sufficiently strong theoretical roots. An environmental philosophy that truly achieves a policy turn, i.e., one that can exert a truly significant influence in environmental policy making, must be based on a unified and robust theoretical paradigm. This paper takes the goals and tasks of environmental philosophy research as an entry point, analyzes the deviation of the development of environmental philosophy in China to the problem of the intrinsic value argument, and explores the new direction of environmental philosophy research by focusing on the central argument of environmental pragmatism. In order to deeply explore this issue, this paper takes the Marxist concept of development as the theoretical guide and mainly adopts the methods of inductive research, comparative research, and theory to practice. This paper summarizes the foundation of contemporary environmental philosophy into four basic questions of center, value, ethics, and survival and seeks answers to these questions in philosophical thought. To construct the basic framework of modern Chinese environmental philosophy, through the comparative study of environmental ethics in different periods, this paper explores the relationship between environmental ethics in the perspective of Marxist concept of development, so as to further clarify the development direction of environmental ethics in China in the future. [ABSTRACT FROM AUTHOR]

Facing the severe employment situation and social environment, the employment of college students has become a very important issue. The big data analysis plays a positive role in entrepreneurship, which can not only improve the success rate of entrepreneurial path selection, but also accumulate a lot of innovative practical experience for college students. Based on the importance of big data technology for entrepreneurial path, this paper proposes an innovative model of accurate support path for college students' entrepreneurship (CSE), in which the K-means algorithm is applied to the analysis of entrepreneurial support path. Finally, this paper makes an experimental analysis on the model, and the results show that K-means can greatly reduce the computational complexity of the algorithm, and the precision, recall, and F parameter of the model can be effectively improved. The model is of great significance in improving the feasibility of college students' entrepreneurial support policies. [ABSTRACT FROM AUTHOR]

It is the responsibility of colleges and universities to nurture talents for the country. In the final analysis, the purpose of teaching, scientific research, and social services in colleges and universities is to educate people. The study of labor education, in the face of the important historical opportunity of transformation, is a theoretical representation of labor education and its value choice. The answer to this question can help us clarify the meaning of labor education and improve the scientific and systematic practice of labor education. Labor education in colleges and universities has an important and extensive value significance for cultivating contemporary college students, which can not only inspire students to study hard in science and culture, master their skills, and grow their talents but also guide them to firm ideals and beliefs, exercise good character, and cultivate the emotional experience of labor so that contemporary college students can integrate the pursuit of life values with the great cause of national prosperity and national rejuvenation and integrate the beautiful vision of personal ambition and family happiness with the good cause of collective, social, and national interests. This paper is based on the background of the times. Therefore, this paper studies the labor culture and ecological environment from the background of the times: the path of renewing the concept of "cultivating talents for the nation" in labor education. It also gives a profound discussion on labor education in high schools and finally puts forward relevant suggestions for the problems. [ABSTRACT FROM AUTHOR]

The cultural industry of ethnic minorities carries the wisdom of many ancients. In today's modernization, ethnic minority cultural industry products can still impress people's hearts with exquisite handicrafts, natural materials, and strong culture. The rise in demand for ethnic cultural products will bring about an increase in the demand for raw materials for handmade products, which is bound to have an impact on the environment. This paper is aimed at modeling and analyzing the ecological level of minority cultural industries based on the background of the Internet of Things (IoT) and environmental responsibility. In the experiment, this paper analyzed the ecological level of the traditional fish skin industry by taking the Hezhe people in Heilongjiang as an example. Aiming at the cultural industry of the Hezhe people, this paper selected the fish skin industry as the object of empirical analysis from the fish culture it represents. According to the ecological level of the industry, this paper selected the three first-level indicators of production energy saving level, ecological environmental protection level, and production emission reduction level and its 12 subordinate second-level indicators to model and analyze the fish skin industry of the Hezhe people. The analysis results showed that the industrial ecological level of the Hezhe fish skin industry in the past 16 years reached the standard rate of more than 75%. However, the ecological level index for the three years of 2018, 2019, and 2020 was between 0.3 and 0.5, which indicated that the ecological level in these three years was very low. This was caused by the mechanization of the handicraft industry in recent years. [ABSTRACT FROM AUTHOR]

In order to further develop and improve the management theory of public libraries, this paper studies the impact of library information on the utilization of regional environmental resources from the perspective of intelligent adaptive learning. Firstly, based on the data envelopment analysis method, this paper measures the efficiency of Public Libraries in various regions of China. Then, using Tobit model, this paper analyzes the environmental factors affecting the efficiency of public libraries from three aspects: financial allocation, per capita GDP, and per capita years of education. The results show that there is a significant correlation between per capita GDP, per capita years of education, and the efficiency of public libraries. There is a significant negative correlation between per capita GDP and public library efficiency (the coefficient is -5.73x10-6, and the probability of two-sided t-test is 0.0229); There is a significant positive correlation between the number of years of education per capita and the efficiency of Public Libraries (the coefficient is 0.0684, and the probability of two-sided t-test is 0.0169). Conclusion: This study provides a reference for the performance evaluation of provincial public libraries. [ABSTRACT FROM AUTHOR]

Agriculture is particularly essential in the equilibrium between man and nature because of its intimate contact with nature. So the cornerstone for the sustainable development of the human economy and society is the sustainable development of agriculture. When it comes to global trade, agricultural trade has always been in a very special position. The basic situation of agriculture involves food safety, environmental protection, Chinese politics, and many other issues. In order to overcome the problems of overlapping, repetitive, and too many indicators in the evaluation method of agricultural environmental sustainable development and unfavorable for practical operation, this paper proposes an ecological footprint model based on emergy. The model can effectively evaluate the ability of sustainable development of agricultural environment and solve the problem that traditional evaluation methods cannot comprehensively evaluate. This makes agricultural development sustainable and is conducive to the liberalization of international agricultural trade. The experimental results of this paper show that from 2014 to 2018, the degree of damage to the agricultural environment has increased from 21% to 45%, which has led to a decline in the quality of agricultural products, and the output and sales are not as good as before. It can be seen that only by ensuring the sustainable development of the agricultural environment can we ensure the smooth progress of the international agricultural trade liberalization and make China's economy flourish. [ABSTRACT FROM AUTHOR]

The uniqueness of aesthetic implication in Zhou Dynasty poetics lies in that it is the basic forming stage of the concept of formal beauty of the whole Chinese nation, and the aesthetic implication of the Zhou Dynasty poetics art has fundamental significance for the whole ancient Chinese aesthetic implication theory. In the discipline of natural language processing, text emotion analysis is a crucial topic. Artificial neural network research is where the idea of "deep learning" (DL) first emerged. In view of the problems that semantic information is easy to be lost and emotional information may be ignored in the traditional Chinese short text emotion analysis model, this paper introduces the AM (attention mechanism) and proposes a CNN-LSTM (convolutional neural network-long short-term memory) poetic aesthetic implication analysis method based on self-attention. For the IL (input layer), word vectors trained by Word2Vec are used and then input into the CNN-LSTM joint model. Then, the output of the joint model is weighted and summed by self-attention and finally input into the Softmax classifier, so as to realize the emotion classification of the text. By creating and putting into practise pertinent comparative experiments, the usefulness of the proposed model is confirmed. The outcomes demonstrate that this model outperforms the other three comparison models for the quantification of evaluation indices in terms of overall performance. The accuracy and F1 of this paper are 93.362% and 90.886%, respectively, which are higher than other models. [ABSTRACT FROM AUTHOR]

In order to analyze the evolution trend of public opinion in emergencies and explore its evolution law, this paper constructs a network sentiment analysis model based on text clustering, where the emotion analysis part is based on the pretraining BERT model and BiGRU model, in which BERT is used as the word embedding model to extract the feature vector of emotional text and BiGRU is used to extract the context of the text feature vector to accurately identify the sentiment polarity of public opinion data. In addition, the K-means clustering algorithm and Kolmogorov-Smirnov Z test were used to divide the different epidemic stages. Compared with other methods, the model proposed in this paper has a great degree of improvement in accuracy, recall, and F1 score index, which provides an opportunity reference and effective detection means for schools at all levels to carry out timely mental health education and psychological intervention for students. [ABSTRACT FROM AUTHOR]

Green and smart cities are based on clean energy and rely on information technology. They are the guarantee for the realization of efficient and intelligent urban development and green ecological transformation, the basis for sustainable social and economic development, and the inevitable trend of urban development. Therefore, the evaluation of the development level of green and smart cities is of great significance to the development of Chinese cities. This paper has aimed to study the issue of smart city pilots and legal guarantees for green and low-carbon development and introduced the concept of smart city line management, as well as the related theory of entropy weight method, cloud model, and support vector machine algorithm. Based on the sustainable development index system, this paper has combined the low-carbon concept to construct the low-carbon city evaluation index system and carried out an empirical analysis. The sustainable development index system, the research results of low-carbon city, and the current situation and characteristics of low-carbon city construction are studied and analyzed. On this premise, a low-carbon city assessment framework in view of reasonable improvement is built, including low-carbon economy, low-carbon society, low-carbon climate, and low-carbon component. The experimental results of this paper show that the low-carbon environment subsystem has the best coordinated development among the four subsystems, and the current state is the best. By 2021, the coordination degree value has reached 0.6656, which is in a relatively coordinated state. [ABSTRACT FROM AUTHOR]

From the perspective of ecological environmental protection, higher education can not only train a large number of professionals dedicated to environmental protection for the construction of environmental quality, but more importantly, it can promote the improvement of the quality of ecological civilization in the whole society, so as to achieve the effect of indirectly improving environmental quality. BRICS economies, as the most important economies in the world, have an impact on the development of the world in many aspects. However, under the guidance of the concept of sustainable development, whether the environmental quality of BRICS economies meets the standards has also become the focus of scholars. Starting from the sustainable development path, this paper summarizes the model of environmental education in BRICS national higher education. At the same time, through the establishment of the BRICS environmental quality assessment system, the environmental quality of the BRICS countries after the implementation of environmental education was assessed based on the content of the sustainable development system. This paper performs matrix operations on the weight values of the indicators at all levels and the membership vector to obtain a 4 × 4 matrix, that is, the evaluation result Q of each indicator is [0.050, 0.200, 0.113, 0,011], which proves that the evaluation results in this paper are basically reasonable. It can be seen that in terms of forest coverage and environmental protection areas, environmental education in higher education has the deepest impact on Russia. In terms of carbon emissions, South Africa benefits the most from environmental education in higher education, so each country should take corresponding actions according to different environmental assessment results. [ABSTRACT FROM AUTHOR]

In the era of global development, due to the destruction of the environment by traditional production, traditional industries have been forced to open the road of green growth transformation. What kind of methods that can effectively promote sustainable green growth has become one of the current research topics that has attracted much attention. Addressing this issue is very important for the green growth sector. With the in-depth research on green growth, the research on the promotion of green growth by political institutions has gradually been carried out, and its policy advantages are of great significance to solve the problem of green growth transformation. The purpose of this paper is to examine the role of law in the promotion of sustainable green growth by political institutions. Through the analysis and research of sustainable green growth, law, and logistic regression model, it can improve the level of sustainable green growth of enterprises and solve the problem that the current level of sustainable green growth of enterprises is not high. This paper analyzes sustainable green growth, the role of law, and logistic regression models and uses relevant formulas to explain them. The experimental results show that the green growth index of group A production enterprises is higher than that of group B. Legal means have played a very important role in improving the level of sustainable green growth in the promotion of sustainable green growth by political institutions. It can meet the requirements of green growth under the current SDG concept, and its sustainability has been greatly improved. [ABSTRACT FROM AUTHOR]

Financial innovations emerge in an endless stream, and it is difficult for the regulatory measures and efforts of banks in various countries and the credit risk management level of commercial banks themselves to adapt to the increasingly complex risk environment faced by banks. In the process of building GFR (green financial risk) mixed governance model, the division of powers and responsibilities of governance subjects should be effectively defined. Therefore, it is very necessary to comprehensively and systematically study and grasp the characteristics, performance, and causes of commercial banks' GFR and build an early-warning model of commercial banks' GFR to comprehensively monitor the risks of banks, so as to reduce risks and avoid crises. Therefore, this paper uses the forward three-layer BPNN (BP neural network) technology to establish a real-time warning model of commercial banks' GFR. IL (input layer) to HL (hidden layer) adopts Sigmoid function, while HL to OL (output layer) function adopts linear function Purelin function. The results show that the test result of this method is greatly improved compared with the traditional method, and the correct rate is increased from 81.27% to 94.38%. It shows that the model in this paper has achieved a good warning effect of GFR for commercial banks. [ABSTRACT FROM AUTHOR]

The structure of fiscal expenditure in China has been suffering from over-reliance on a single type, while synchronisation and coordination with economic growth are lacking. This paper studies and analyses fiscal expenditure and green from a theoretical perspective. There is a close link between the structure of fiscal expenditure and green economic growth, and a reasonable and appropriate selection and allocation is conducive to promoting the overall development level of China, while financial resources input is a key consideration in optimising the structure of fiscal expenditure. This paper proposes hypotheses and establishes a regression model after an in-depth study of fiscal expenditure in a provincial economy in Asia in the light of domestic and international literature. Through empirical analysis, a green GDP reflecting economic growth and environmental pollution is synthesised using the principle of output per unit of pollution, and the impact of fiscal expenditure structure on green economic growth in China is empirically tested. [ABSTRACT FROM AUTHOR]

There are a lot of environmental protection musicals and dances in public entertainment life to support the concept of environmental protection and to entice people to support the cause of environmental protection. As we all know, in a musical performance, the distance between the audience and the actors, the design of the stage environment, the training of the actors, the costumes of the actors, the makeup of the actors, and the musical accompaniment will all have more or less influence on the stage performance effects. In order to make environmental protection music and dance dramas profoundly meaningful to social production and human activities, it is especially important to analyze the stage performance of such music and dance dramas. The analysis of stage performance effects is not only beneficial to making the ideas spread by the music and dance drama penetrate into people's hearts but can also provide guiding suggestions for the production of music and dance drama. Therefore, this paper proposes a linear regression algorithm based on artificial intelligence to deeply explore and analyze the influence of the above six factors on the stage performance effects of environmental protection music and dance drama. In our method, first we preprocess the data collected by classification to remove the odd values from the data so that the various types of data conform to a normal distribution. Secondly, we obtained linear fit plots of the six factors with the stage performance effect scores by using a linear regression algorithm to deeply analyze the correlation between various types of data and the stage performance effect scores. Finally, through numerical calculations, we found that the distance between the audience and the actors, the training of the actors, and the musical accompaniment have a greater influence on the performance effect of the musical cabaret in the environmental protection category. Meanwhile, the costumes of the actors, the makeup of the actors, and the design of the stage environment have less influence on the performance effect of the musical cabaret. Therefore, in the production and performance of environmental protection music and dance dramas, producers and performers should pay more attention to the distance between the audience and the actors, the design of musical accompaniment, and the training of actors. To sum up, this paper has made a scientific, detailed, and reasonable analysis of the performance effect of environmental protection music and dance dramas on stage, contributing to the dissemination of environmental protection ideas. [ABSTRACT FROM AUTHOR]

In recent years, college students' psychological problems have occurred frequently, and the early warning of college students' psychological crisis has received social attention. Artificial intelligence and big data, as emerging technologies that have attracted much attention in recent years, have broad application and development space in improving the development of intelligent and refined education in colleges and universities. Applying artificial intelligence and big data to the practice of college students' mental health education plays a very positive role in accurately finding and scientifically solving college students' mental health problems. This paper combs the current application and research of artificial intelligence and big data in college students' mental health education and then clarifies the problems existing in the practical application. Finally, on the basis of in-depth analysis of the characteristics of college students' psychological crisis, the paper designs college students' psychological crisis early warning data collection system from six aspects, including the educational administration system and the access control system. And from the aspects of establishing a multilevel linkage feedback early warning system, building a team of big data technical personnel and mental health education personnel, it puts forward countermeasures for college students' psychological crisis, so as to provide theoretical and methodological support for college mental health management. [ABSTRACT FROM AUTHOR]

Heidegger is not actually an antitechnologist or a revivalist. He does not think we need to escape from technology while criticizing it, nor does he miss a certain "golden age" in human history. Heidegger cannot provide us with specific methods to solve many problems in the technological age, but his reflection and questioning provide us with a possible way of redemption, which is of great significance to the development of our current era. After analyzing Heidegger's related works and related literature by many scholars, this paper finds that most of the research stays on aspects such as the existence, the nature of art, the nature of technology, the crisis brought about by technology, and the rescue of technology by art. Part of it involves the relationship between technology and art, but rarely concentrates on thinking about the relationship between technology and art. Based on this, through the exploration and analysis of the origin of ancient techniques and the reconsideration of the essence of modern technology, this paper takes the "Ge-stell" thought in the context of Heidegger's thinking on technology as the breakthrough point and reexamines technology. It understands and expounds the development of art; tries to study the inner connection and connotation between Heidegger's modern technology, art, and modern technology "Ge-stell"; and grasps the relationship between technology and art as a whole. By analyzing and pointing out the "Ge-stell" essence of technology, the blood relationship between technology and art has been cut off, and art has been brought into the control of technology, resulting in an unprecedented survival crisis for human beings. Finally, the rescue in the technological era is proposed. It can provide philosophical guidance and new thinking for the development of the current society and the plight of the times it is facing. [ABSTRACT FROM AUTHOR]

In the context of the new era, the distinctive function of BD (big data) analysis and prediction also introduces a new way of thinking to university IPE (ideological and political education), broadens the domain of university IPE, and enhances the curricular offerings of IPE universities. In order to enhance the intelligence and personalization of the intelligent teaching system, this paper describes in detail the design and implementation processes for each component of the system. It also uses the association mining rule algorithm of data mining. To maintain population diversity, a population initialization method and a neighborhood-based search operator are used, both of which are based on a thorough consideration of the characteristics of complex networks. The neighborhood search strategy enhances the local search capability of the TLBO (Teaching-Learning Based Optimization) algorithm. The optimized TLBO algorithm presented in this paper achieves the highest average modularity value of 0.5238 through testing on real-world data sets. The outcomes demonstrate that the algorithm performs well and is successful in identifying problems in the community. [ABSTRACT FROM AUTHOR]

Artificial intelligence technology has become an important part of the development of Internet technology. Artificial intelligence technology can help colleges and universities to continuously optimize the English teaching system. This technology can help colleges and universities to carry out English education in the field of public health and can improve the overall quality of English teaching in colleges and universities. Artificial intelligence technology is related to the optimization of English teaching environment in colleges and universities. At the same time, artificial intelligence technology also affects the development of society and the future of the country. Artificial intelligence technology provides more accurate data resources for English teaching in the field of public health in colleges and universities. It also provides rich and reliable educational technology means for teachers. This technology improves the scientific nature of English education in the field of public health in colleges and universities. This paper comprehensively uses a variety of methods such as case empirical analysis and qualitative analysis to analyze the application mode of artificial intelligence technology in English teaching. This paper closely integrates artificial intelligence technology with English education in the field of public health in colleges and universities. College English teaching methods, teachers' personal factors, and teacher-student relationship will all have an impact on students' health. This paper makes a comprehensive analysis of the theoretical basis and actual situation of English teaching in colleges and universities, and then constructs an innovative system of English education in the field of public health in colleges and universities. Based on this, the text adopts a structured analysis method to conduct an in-depth analysis of the application mode of artificial intelligence technology. This paper analyzes in detail the opportunities and challenges faced by the development of public health education in colleges and universities. At the same time, this paper also summarizes the objective laws of the development of public health education, and then comprehensively analyzes the impact of artificial intelligence technology on the English education model in colleges and universities. [ABSTRACT FROM AUTHOR]

The heart and soul of the Chinese people and the greatest cultural soft power of contemporary China are excellent Chinese healthy cultural environments. Short video platforms and short videos have a chance to develop as the Internet revolution continues to intensify and mobile clients gain popularity. This essay examines the challenges involved in producing brief videos that promote a healthy cultural environment in the new context of internet plus, as well as the means of transmitting such videos and creative methods for doing so. Excellent communication content is created in this paper from two perspectives of visual presentation and in-depth meaning, allowing users to fully understand the connotation of a healthy cultural environment. Through the theme of a healthy cultural environment, topic discussion and characteristic activities will be carried out to encourage users' spontaneous sharing of the interactive behavior of communication and the fission communication of brief videos of a healthy environment. This paper develops a model for intelligent recommendation and short video content analysis based on this. In order to further encourage the creative dissemination and development of short videos about healthy cultural environments, the model is used to choose high-quality videos and accurately recommend them to the appropriate users and to serve as an example of how a quick video can be used to communicate innovation and a healthy cultural environment. [ABSTRACT FROM AUTHOR]

The rapid development of Internet technology has promoted the vigorous development of the multimedia. As one of the most classic instruments, the violin has been fully developed in its creation, education, and performance. In the face of more and more violin performances, the effective organization and retrieval of these musical works is an urgent problem to be solved, while it is common to classify and organize music based on the emotional properties of the performance. Deep learning is a model based on feature hierarchy and unsupervised feature learning, which has strong learning ability and adaptability. Based on the recurrent neural network (RNN) method, long short-term memory (LSTM) is one of the classic models of deep learning that can effectively learn the characteristics of time series data and achieve effective predictions. Therefore, based on the classical Hevner emotion classification model, this paper proposes an emotion recognition method for dynamic violin performances based on LSTM, which selects acoustic features and classifies the audio acoustic signals contained in the violin performances. In order to verify the effectiveness of this method, this paper carries out data labeled, feature selection, and model test on the actual violin music data by turn. The results show that the proposed method can greatly reduce the training time and improve the prediction accuracy, which reached 83%, higher than the existing methods. Meanwhile, the accuracy and iteration times of violin playing music of different emotional categories are also counted. Moreover, the method is robust to the genre, timbre, and noise changes, and the emotion recognition effect is superior. [ABSTRACT FROM AUTHOR]

In the quality evaluation of public sports training, the selected indicators are not comprehensive, resulting in some errors in the results of quality evaluation. Therefore, this paper designs a public sports training quality evaluation method based on the deep learning model of global topology optimization. Determine the basic principles of public sports training quality evaluation, determine the human coordinate points of public sports training by determining the basic section and basic axis of human training, and extract the data of public sports training quality evaluation. On this basis, quantify the public sports training quality evaluation index, construct the evaluation matrix, calculate the weight of the evaluation index, and determine the importance of the public sports training quality evaluation index. Preprocess the public sports training quality evaluation index set, search the optimal fitness value in the global topology optimization depth learning model, introduce the global topology optimization depth learning model, input the evaluation index and output the evaluation quality results, and realize the quality evaluation of public sports training. The experimental results show that the evaluation method in this paper can improve the accuracy of the evaluation results and is feasible. [ABSTRACT FROM AUTHOR]

Based on the theory and application, this paper discusses the optimization of art image segmentation algorithm based on FFNN (Feed Forward Neural Network). In this paper, residual units are used in the corresponding stages of encoder and decoder, and feature information of several convolution layers in each convolution stage of encoder is extracted at the same time. And the feature pyramid module is used to extract multiscale features from the feature map of the last convolution stage in the encoder. Finally, pixel by pixel additions combine the previously mentioned feature information into the corresponding layer of the decoder. Additionally, an improved weight adaptive algorithm based on feature preservation is suggested in this paper, which addresses the issue that the conventional image segmentation algorithm is noise-sensitive. The adaptive connection weight mechanism is also introduced. The accuracy and recall rates of this optimization algorithm can both reach 96.574%, according to the results of 50% cross-validation. All the segmentation performance evaluation indexes of this algorithm are higher than the existing main algorithms. Moreover, the algorithm takes a short time, does not need too much manual intervention, and can effectively segment artistic images. The optimization algorithm in this paper has certain reference significance for the related research of artistic image segmentation. [ABSTRACT FROM AUTHOR]

Food has an impact on everyone's daily life, the long-term stability of the nation, human survival and development, people's lives and health, and the steady advancement of society. A food safety criminal judgment is a legal document used to record the trial of food-related offences. It primarily contains the case's history, information about the parties involved, and the verdict. In order to identify defendants, their charges in court documents, and other important court information, this paper proposes a method for extracting key information from food safety criminal conviction documents based on deep learning. It builds and analyses a hidden Markov model (HMM) based on the corpus of crime-related components, and uses the model trained by a DL neural network to determine the trend of a given data set. In the test result classification task, the results demonstrate that the Transformer model can achieve macro accuracy rates of roughly 0.963, macro recall rates of 0.932, and macro F1 scores of 0.958. Experiments demonstrate the model suggested in this paper's performance and effectiveness in extracting abstract information from food criminal trial documents. [ABSTRACT FROM AUTHOR]

The water environment is one of the basic elements that constitute the environment. It is an important place for the survival and development of human society, and it is also the most seriously disturbed and damaged area by humans. The pollution and destruction of water environment has become one of the major environmental problems in the world today. The essence of urban water space landscape design under the concept of integrating people's ecological design is the ecological landscape design of urban water spaces, while the development of ecological landscape design in the field of urban water space landscape design is still in its infancy, and the interpretation of its concept is also different. The ecological design of the landscape reflects a new dream of human beings, a new aesthetics and value: the true cooperative and fraternal relationship between man and nature. At present, the ecological design of urban water space landscape has not put forward a more accurate concept, clear principles and standards, and a complete and systematic theoretical basis, which requires further research, discussion, and continuous practice by this generation of designers to improve it. To this end, this paper proposed a research method on the integration of water environment governance in urban and rural spaces with natural ecological landscape design. This paper mainly talked about the status quo of water environment and its network sensor algorithm research and analyzed its coverage area one by one. Then, the water quality extraction is introduced in detail. And finally, the data analysis of the Beijing river waters, the analyzer rainfall, water quality, and so on are carried out in the experimental part. It could be seen from the experimental results that there were currently 22 reclaimed water plants in six urban areas of Beijing, with a daily water treatment capacity of 4.08 million cubic meters and a sewage treatment rate of 98%. As of 2016, 440 million cubic meters of reclaimed water has been reused. With the commissioning of the new reclaimed water system, the proportion of reclaimed water in the river and lake environment will continue to increase. [ABSTRACT FROM AUTHOR]

Yan'an is one of the "two holy places" of the Chinese nation and the Chinese revolution and is one of the first cities of historical and cultural significance and an outstanding tourist city in China, as announced by the state council. The evaluation of the effectiveness of environmental conservation is one of the very important elements of the conservation of Yan'an's architectural heritage. However, the existing evaluation methods cannot provide new solutions for decision-making, the meaning of the comprehensive evaluation function is unclear, the naming clarity is low, there is less quantitative data and more qualitative components, and the results are not easily convincing. This paper proposes a method for evaluating the practical effects of environmental class measures in the conservation of Yan'an's architectural heritage based on recurrent neural networks. The recurrent neural network makes full use of the memory function in the network, considers the causal relationship of the actual effect, and efficiently evaluates the existing measures. In comparison with factor analysis and hierarchical analysis, this paper has greater applicability in evaluating the practical effects of environmental measures in the conservation of Yan'an's architectural heritage and is basically consistent with the results of the theoretical analysis. It provides a scientific basis for the construction and implementation of environmental measures for the architectural heritage of Yan'an. [ABSTRACT FROM AUTHOR]

In recent years, there has been a lot of news about college students committing suicide. In the university stage students, self-esteem is stronger and more sensitive, and the ability to withstand pressure is weak. At the same time, college students are in a key stage of mental health development. School education to a certain extent for the cultivation of students' mental health has a crucial impact. In our country, it is undoubtedly the main way to infiltrate mental health education through subject knowledge teaching. French teaching is a good way to infiltrate mental health education. In the learning practice, the improvement of students' mental health levels can strengthen their interest in French learning. Based on this, this paper, from the perspective of French teaching, carries out the infiltration of mental health education in French teaching classes in universities and promotes the cultivation of students' learning abilities and the development of mental health. This paper mainly studies the feature extraction of mental health data, tries to use the optimized BP (backpropagation) neural network to infiltrate the mental health model of college students, and describes the differences in mental health among students. Finally, the results are applied to French teaching in universities, and a good teaching effect is achieved. Finally, the experimental results show that the infiltration strategy proposed in this study is feasible and effective. [ABSTRACT FROM AUTHOR]

The rapid development of social economy will promote the development of sports industry and then have an impact on sports economy. By using the regression analysis method, this paper compares the influencing factors of sports industry development, aiming at exploring the influence of sports industry development on economic development and its future development trend. This paper takes 12 industries of sports industry development from January 2020 to January 2022 as research objects, compares the development of sports industry of different research objects, and determines the factors affecting sports industry. We compare the promotion of different factors to sports economy and provide support for the formulation of sports industry development measures. The results show that economic growth, sports industry types, the degree of integration between sports industry and economic development, sports industry action time, and sports industry scale are the main factors affecting sports industry and promote the development of sports economy. The above indexes can improve the economic level of sports industry, and the improvement degree is about 10∼20%. Therefore, local governments and sports organizations should formulate measures to promote the economic development of sports industry from the aspects of economic growth, sports industry types, integration degree between sports industry and economic development, action time of sports industry, and scale of sports industry. [ABSTRACT FROM AUTHOR]

The ecological problems faced by China's environmental protection are becoming more and more serious. Serious haze occurs frequently in some areas. Water pollution, soil pollution, and other new types of pollution are still relatively prominent problems. Therefore, rural architectural planning and landscape optimization design should be based on the premise of ecological environmental protection. This paper puts forward the evaluation of rural architectural planning and landscape in the context of ecological environment protection and uses the analytic hierarchy process to analyze and obtain the evaluation results. This method has a comprehensive and scientific powerful evaluation function. The experimental results of this paper show that after the evaluation of the analytic hierarchy process, it is found that the comprehensive score of the architectural planning and landscape of village A is not very high. The highest weight is 0.3210, the landscape diversity score of street A is 1.28, and the landscape diversity score of street D is 1.76. This is the highest score, indicating that the architectural planning and landscape of the village cannot meet the needs of contemporary ecological environmental protection. Aiming at the problems existing in the landscape, the corresponding measures are also given at the end of the experiment, which has certain significance for the landscape optimization design. [ABSTRACT FROM AUTHOR]

Cross-media narrative of school culture is essentially different from emotional identity. We cannot just rely on students' rote learning to achieve this teaching goal, but we must let students gradually deepen their learning experience in the learning process. As a new narrative form in the context of media convergence, its narrative strategy from the perspective of media convergence culture can promote the industrialization of IP cultural resources, such as content production, marketing and dissemination, and derivatives development. This paper mainly studies the cross-media narrative and emotional identity of school education culture through wavelet transform algorithm. The research shows that the error rate of this paper is the lowest among the three methods, with the highest error rate of 46.8%, followed by the method of literature Sara 2018 with the highest error rate of 64.8%, and finally the method of literature Neate et al. 2017 with the highest error rate of 71.8%. It can be seen that this method is the most suitable for identifying the emotional characteristics of school education culture. Through wavelet transform, teachers can infiltrate the basic knowledge of Chinese into the cultivation of students' emotions in the teaching process, which is conducive to students' emotional edification, personality development, and self-motivation. [ABSTRACT FROM AUTHOR]

Both dynamic and interactive, cross-cultural education emphasizes respect, interaction, and understanding between various cultural groups. Its fundamental principle is to acknowledge and value cultural diversity while opposing attempts to artificially unite cultures in order to recognise the equality and common heritage of all cultures. The goal of intercultural education, from an individual's perspective, is to support those who are educated in understanding, accepting, and respecting other foreign cultures in order to better adapt to and thrive in a multicultural society. To develop students' intercultural communication skills is the goal of intercultural education. Based on the associations between intercultural education and speculative reading, this essay analyzes the crucial role that intercultural English teaching and speculative reading instruction play in colleges and universities before going over the situation and approaches that English speculative reading instruction is currently facing. This paper primarily discusses the data on students from the student work management system, the relationship between grades and actual behavior, and the rules that are mined to provide a scientific basis for decision-making for the relevant units in colleges and universities. According to experimental analysis, the data mining algorithm in this paper performs better than the other two in terms of predicting students' English achievement, with an average accuracy of 0.86 compared to 0.71, 0.075, and 0.73 for the other three algorithms. The decision tree created using this methodology can quantitatively reflect the impact of different teaching factors on learning quality and offers a clear and reliable foundation for formulating targeted improvement strategies. [ABSTRACT FROM AUTHOR]

Many IP (intellectual property) will also be infringed, and it will become more and more serious, causing huge economic losses to people or groups who own IP. If punitive damages can be made for intentional but intentional infringement of IP, it will help to stop intentional infringement of IP, and it can also give due compensation to the obligee's loss. Based on this, this paper analyzes the introduction and implementation of punitive damages in IP law. In this paper, a relatively efficient text classification method is realized by using the method of deep learning and model design. Similar texts in the training set are grouped into a group, and each group is considered as a common text vector. Then, a threshold is set to deal with clusters higher than the threshold, and the training set is reformed. Through the experimental results, the feature extraction effect of this model is improved, the classification accuracy is constantly improved, and the final convergence rate of this model reaches 95%. It has been verified that the system can realize the automatic classification of basic Chinese patent texts. [ABSTRACT FROM AUTHOR]

The tertiary industry occupies a large area in China's economic system, and it plays an important function in the growth of China's economic development. It is of positive significance to study the relationship between emotional labor and occupational self-efficacy of singing artists in the tertiary industry. This paper mainly studies the correlation between the emotional labor of singing artists and their professional self-efficacy and analyzes the strength of the correlation. This paper selects 150 singing art personnel in the singing art association in city A to conduct a questionnaire survey and conducts data processing on the questionnaire. This paper explores the influencing factors of emotional labor and four dimensions of occupational self-efficacy. This paper firstly analyzes the differences of the influencing factors of emotional labor and then tests the interaction of the different factors selected. It then conducts a significant test on the four dimensions of professional self-efficacy and finally studies the correlation between the two based on the previous analysis results. This paper concludes that there is a highly significant relationship between the emotional labor and professional ego efficacy of singing artists. And the correlation coefficient and determination coefficient are 0.293 and 0.087, respectively. It shows that 8.7% of the total variance in occupational self-efficacy variables can be explained by emotional labor. There was no significant correlation between surface acting and occupational self-efficacy. Deep acting has the greatest correlation with the physical and mental efficacy dimension of occupational self-efficacy, with a correlation coefficient of 0.391. There were significant correlations between natural performance and the four dimensions of occupational self-efficacy. The highest value is interpersonal efficacy, which is 0.337. The research conclusions of this paper have certain reference value for exploring the relationship between emotional labor and professional self-efficacy of singing artists. [ABSTRACT FROM AUTHOR]

The ongoing integration of IT with various disciplines is a result of IT's constant penetration of the educational sector. This paper investigates how to further promote the deep integration of IT and political thought courses in institution of higher learning based on the fragmented learning background, starting from the current teaching situation of political thought courses in institution of higher learning, based on modern educational theory and supported by IT. Strengthening the relevance and affinity of political thought courses in institutions of higher learning and more effectively implementing the political thought instructional resource are examples of new approaches that can be explored to increase the effectiveness of political thought education and teaching. The integration model of political thought course instructional resources in higher education institutions is also constructed in this paper. According to the user's interest characteristics, the instructional resources are filtered, and the search service and recommendation service of political thought instructional resources are few but adequate. This model introduces personalized information service based on network into the instructional resource system, learning, and tracking users' personalized interests. The results of the experiments demonstrate that this algorithm has an accuracy of up to 95.03 percent. IT has a certain degree of applicability and dependability, and this study can offer valuable reference material for the deep integration of IT and political thought teaching in institutions of higher education against the backdrop of fragmented learning. [ABSTRACT FROM AUTHOR]

Since demand forecasting is the first step in managing and operating a tourism business, its accuracy is very important to tourism businesses. In order to address NN's drawbacks, such as local optimization, slow convergence, and large sample sizes, this paper organically combines the PSO and NN models and builds a PSO-NN-based tourism demand forecasting model. The tourism demand forecasting indexes, the choice of NN forecasting models, the modelling process, and the implementation methods are first analysed and studied along with the fundamental theories and forecasting techniques of PSO and NN. In order to increase the precision of the prediction model, the PSO algorithm is also used to optimise the weights and thresholds of the NN. The final section of the paper compares the performance of the model developed in this paper with the most widely used model for forecasting tourism demand. According to the experimental findings, this model's prediction accuracy can reach 95.81 percent, or about 10.09 percent higher than the prediction accuracy of the conventional NN model. There are some practical implications to this research. Applying the optimization model to the forecast of tourism demand is doable and practical. [ABSTRACT FROM AUTHOR]

The big data (BD) era and pertinent computer science, pedagogy, and educational psychology knowledge are the foundations of this essay, based on the idea of the holistic development of human beings, the IPE (Ideological and Political Education) carrier theory, the new idea of educational development, and the strategy of strengthening the nation through education; the challenges IPECU (Ideological and political education in Colleges and Universities) faces and its path toward optimization are discussed relatively in detail in this paper, which conforms to the context of mega data thinking. The influence of IPECU's subject, object, and educational effect is discussed in this paper, along with tips for how to improve and innovate IPECU in the context of big data. In addition, it is noted that in the age of mega data, we must not only bravely take on challenges, but also actively seize opportunities if we are to realize the innovative and optimized development of IPECU. Moreover, the definitions of mega data and big data prediction function are provided in this paper. IPE can be used with the big data prediction function, which is further explored in this article. In order to realize the innovation of IPE mode in universities, this paper aims to encourage the integration and development of IPE and big data in academic settings. [ABSTRACT FROM AUTHOR]

With the development of society, the number of autistic children in China is increasing, which not only makes the family's happiness very low, but also seriously affects the development of teenagers and society. Among the symptoms of autistic children, early childhood communication skills have received extensive attention. In traditional rehabilitation training, with a lack of parents' participation, most of the training cannot arouse the interest of autistic children, so the treatment effect is not obvious. Based on this, this paper proposes the application of family sports games to improve the early communication ability of autistic children. This article aims to investigate the role of family sports games in promoting the development of early communication skills in autistic children. This paper uses the fuzzy comprehensive evaluation method to score the comprehensive ability of family sports games. The experimental results of this paper show that before the experiment, the comprehensive scores of children's communication ability in the control group and the experimental group were 18.92 and 18, respectively, which were generally low, and there was no significant difference. This shows that the communication skills of the two groups of children before the experiment are relatively poor. After the test, the children's comprehensive score of communication ability in the experimental group increased by 35.8 points, and the difference was significant, indicating that family sports games have a great impact on the development of children's communication ability. [ABSTRACT FROM AUTHOR]

With the continuous rise of my country's international status, the cultivation of students' cross-cultural thinking ability has become an important goal of college English teaching. Since the twentieth century, theories about critical thinking ability have been abundant, and how to improve students' critical thinking ability is also a hotspot of reform. In foreign countries, there are rich teaching models, but in China, it is still a major problem to be solved to cultivate students' speculative ability through specific teaching methods. How teachers' classroom teaching is related to the cultivation of speculative ability. In addition to having direct application significance for teachers to realize the cultivation of speculative ability in routine teaching, the research on these issues is conducive to opening the "black box" of classroom instruction. The most crucial tasks in teaching speculative reading and cross-cultural education in today's college English curriculum are the only means of enhancing students' critical thinking and cross-cultural communication skills. This paper analyses, researches, and applies the diagnostic evaluation model using data gathered during system usage. In order to enhance the diagnostic evaluation function of the college English diagnostic practice system and the associated test paper generation algorithm, the author then designs and implements two test recommendation algorithms in accordance with the diagnostic evaluation model. [ABSTRACT FROM AUTHOR]

With the rise of Erhu teaching in recent years, a large number of people have joined the team to learn Erhu playing. However, due to the high cost of teaching and the unique one-to-one teaching mode between teachers and students, Erhu education resources are very scarce. Learning Erhu performance has become a luxury activity. Nowadays, with the rise of artificial intelligence, computer music is developing rapidly. Music has two important aspects: composition and performance. Different kinds of instruments convey different styles, and players inject different rhythms and dynamics into their performance, thus producing rich expressive force. The development of image style conversion, which opens people's evaluation of music performance, is an important issue in many fields of artificial intelligence (it is also known as intelligence, machine intelligence, referring to the intelligence shown by the machine made by people. Usually, artificial intelligence refers to the technique of presenting human intelligence through ordinary computer programs). For an Erhu song, there are various factors that affect its effectiveness, and there are many indexes to evaluate it, such as sense of rhythm, expressive force, musical sense, style, and so on. Using a computer to simulate the evaluation process is essential to find out the mathematical relationship between the factors that affect the performance of music and the evaluation indexes. Neural network is a kind of mathematical model proposed by simulating the way of thinking of human brain in artificial intelligence. It has the advantages of not having strict requirements on data distribution, nonlinear data processing method, strong robustness, and dynamics and is very suitable for the mathematical model of evaluation system. In addition, the neural network also has a strong theoretical basis, and their application in various industries has developed basically mature. This paper tries to introduce a deep neural network mathematical model into the evaluation system of Erhu performance, and the experimental results prove the reliability and practicality of the method in this paper. It can provide a method basis and theoretical reference for evaluation of Erhu performance effect. [ABSTRACT FROM AUTHOR]

This paper discusses the structure of psychological well-being education programmes in higher education institutions based on an analysis of the connotation and characteristics of deep learning theory, as well as the background of today's talent training requirements, the psychological traits of contemporary students, and the practical requirements of the teaching reform of psychological well-being education courses in higher education institutions. A model for evaluating the psychological well-being of college students based on BPNN is presented in this paper, which also addresses the current severe shortage of full-time psychological counsellors. Additionally, the traditional BPNN is optimised by GA, and the resulting NN can better achieve the desired effect, demonstrating the viability of BPNN. It enables the psychological well-being of college students to be self-diagnosed online and significantly lessens the workload of psychological counselling institutions in higher education. According to the experimental findings, the optimised algorithm's accuracy can reach 92.47 percent, and it is considered to be reliable. This study not only offers a novel approach to nonlinear data processing, but also paves the way for variable screening in the presence of an ambiguous structure. Additionally, in a limited sense, it offers insightful research for psychological education in higher education institutions. [ABSTRACT FROM AUTHOR]

With the depletion of global resources and the deterioration of the ecological environment, the implementation of green reverse logistics management has become a necessary means. Green reverse logistics is a new type of reverse logistics that aims to improve resource utilization and protect the ecological environment. While promoting sustainable development, "green reverse logistics" also has certain social and economic significance. This paper compared the green reverse logistics system based on blockchain with the current green reverse logistics system. Taking drug recycling as an example, this paper mainly analyzed the waste rate, utilization rate, and enterprise income. The comparison results showed that the efficiency of drug recycling based on blockchain has increased by 20.1% compared with the current stage, and the waste rate has decreased by 16%. The utilization rate has increased by 14%, and corporate income has also increased by 19.5%. It is greatly indicated that green reverse logistics based on blockchain is of great significance to enterprise income and environmental protection, which also produces great social benefits. [ABSTRACT FROM AUTHOR]

With the rapid development of society, the emergence and innovation of network buzzwords continue to emerge. On the rapidly changing social network platform, previous sentiment analysis tasks cannot fully meet the needs of users. This paper aims to study the metaphorical function and affective cognition in Internet English loanwords. This paper proposes a neural network algorithm and conducts a comprehensive analysis of the metaphorical function and emotional cognition of Internet English loanwords. The neural network algorithm has a powerful sentiment analysis function, so the article chooses this algorithm. The experimental results of this paper show that with the popularity of the Internet, more and more people go online. In 2013, the proportion of Internet users was the highest at 23.2%. In 2015, the proportion of Internet users was 38.3%, an increase of 15.1% in just one year. The percentage of people online will reach 68.3% by 2021, indicating that almost half of the people have learned to surf the Internet. This also means that Internet English loanwords have also been developed. The rapid development of loanwords in Internet English is because they have metaphorical functions and express people's emotions. [ABSTRACT FROM AUTHOR]